Grafici andamento Covid-19

Data e Ora ultimo aggiornamento

In [1]:
import datetime

print(datetime.datetime.today())

2020-10-22 15:42:38.713385
In [2]:
from IPython.display import HTML

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 } else {
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<form action="javascript:code_toggle()"><input type="submit" value="Clicca qui per nascondere / mostrare il codice"></form>''')
Out[2]:
In [3]:
import pandas as pd
import numpy as np
from datetime import datetime
import seaborn as sns
import matplotlib.pyplot as plt
import plotly.graph_objects as go
import plotly.express as px


import warnings
warnings.filterwarnings('ignore')
In [4]:
url_r = "https://raw.githubusercontent.com/pcm-dpc/COVID-19/master/dati-regioni/dpc-covid19-ita-regioni.csv"
data_region = pd.read_csv(url_r)
#print(data_region.dtypes)
#print(data_region.isnull().sum())
#print(data_region.shape)
#print(data_region.head())

url_p = "https://raw.githubusercontent.com/pcm-dpc/COVID-19/master/dati-province/dpc-covid19-ita-province.csv"
data_province = pd.read_csv(url_p)
#print(data_province.dtypes)
#print(data_province.isnull().sum())
#print(data_province.shape)
#print(data_province.head())

url_n = "https://raw.githubusercontent.com/pcm-dpc/COVID-19/master/dati-andamento-nazionale/dpc-covid19-ita-andamento-nazionale.csv"
data_national = pd.read_csv(url_n)
#print(data_national.dtypes)
#print(data_national.isnull().sum())
#print(data_national.shape)
#print(data_national.head())

Tabella dei dati degli ultimi giorni

In [5]:
#add daily cases/deaths/recovered columns
data_national['new_cases'] = data_national['totale_casi'].diff()
data_national['new_deaths'] = data_national['deceduti'].diff()
data_national['new_recovered'] = data_national['dimessi_guariti'].diff()
data_national['new_swabs'] = data_national['tamponi'].diff()
data_national['new_unique_tested'] = data_national['casi_testati'].diff()
#add a day/day-1 percentage change for new_cases
data_national['daily_cases_perc_change'] = round((data_national['new_cases'].pct_change(1))*100,2)
data_national['daily_swab_perc_change'] = round((data_national['new_swabs'].pct_change(1))*100,2)
data_national['daily_unique_tested_perc_change'] = round((data_national['new_unique_tested'].pct_change(1))*100,2)
#detect ratio
data_national['detect_ratio_swabs'] = round((data_national['new_cases'] / data_national['new_swabs'])*100,2)
data_national['detect_ratio_cases'] = round((data_national['new_cases'] / data_national['new_unique_tested'])*100,2)
data_national.tail(10)
Out[5]:
data stato ricoverati_con_sintomi terapia_intensiva totale_ospedalizzati isolamento_domiciliare totale_positivi variazione_totale_positivi nuovi_positivi dimessi_guariti ... new_cases new_deaths new_recovered new_swabs new_unique_tested daily_cases_perc_change daily_swab_perc_change daily_unique_tested_perc_change detect_ratio_swabs detect_ratio_cases
231 2020-10-12T17:00:00 ITA 4821 452 5273 77491 82764 3689 4619 240600 ... 4619.0 39.0 891.0 85442.0 59649.0 -15.34 -18.36 -13.18 5.41 7.74
232 2020-10-13T17:00:00 ITA 5076 514 5590 81603 87193 4429 5901 242028 ... 5898.0 41.0 1428.0 112544.0 70260.0 27.69 31.72 17.79 5.24 8.39
233 2020-10-14T17:00:00 ITA 5470 539 6009 86436 92445 5252 7332 244065 ... 7332.0 43.0 2037.0 152196.0 87601.0 24.31 35.23 24.68 4.82 8.37
234 2020-10-15T17:00:00 ITA 5796 586 6382 92884 99266 6821 8804 245964 ... 8803.0 83.0 1899.0 162932.0 98542.0 20.06 7.05 12.49 5.40 8.93
235 2020-10-16T17:00:00 ITA 6178 638 6816 100496 107312 8046 10010 247872 ... 10009.0 55.0 1908.0 150377.0 92402.0 13.70 -7.71 -6.23 6.66 10.83
236 2020-10-17T17:00:00 ITA 6617 705 7322 109613 116935 9623 10925 249127 ... 10925.0 47.0 1255.0 165837.0 103326.0 9.15 10.28 11.82 6.59 10.57
237 2020-10-18T17:00:00 ITA 7131 750 7881 118356 126237 9302 11705 251461 ... 11705.0 69.0 2334.0 146541.0 95554.0 7.14 -11.64 -7.52 7.99 12.25
238 2020-10-19T17:00:00 ITA 7676 797 8473 125530 134003 7766 9338 252959 ... 9337.0 73.0 1498.0 98862.0 65824.0 -20.23 -32.54 -31.11 9.44 14.18
239 2020-10-20T17:00:00 ITA 8454 870 9324 133415 142739 8736 10874 255005 ... 10871.0 89.0 2046.0 144737.0 87680.0 16.43 46.40 33.20 7.51 12.40
240 2020-10-21T17:00:00 ITA 9057 926 9983 145459 155442 12703 15199 257374 ... 15199.0 127.0 2369.0 177848.0 106488.0 39.81 22.88 21.45 8.55 14.27

10 rows × 27 columns

In [6]:
#regional data preparation

data_region_Abruzzo = data_region[(data_region['denominazione_regione'] == 'Abruzzo')]
data_region_Basilicata = data_region[(data_region['denominazione_regione'] == 'Basilicata')]
data_region_Bolzano = data_region[(data_region['denominazione_regione'] == 'P.A. Bolzano')]
data_region_Calabria = data_region[(data_region['denominazione_regione'] == 'Calabria')]
data_region_Campania = data_region[(data_region['denominazione_regione'] == 'Campania')]
data_region_EmiliaR = data_region[(data_region['denominazione_regione'] == 'Emilia-Romagna')]
data_region_Friuli = data_region[(data_region['denominazione_regione'] == 'Friuli Venezia Giulia')]
data_region_Lazio = data_region[(data_region['denominazione_regione'] == 'Lazio')]
data_region_Liguria = data_region[(data_region['denominazione_regione'] == 'Liguria')]
data_region_Lombardia = data_region[(data_region['denominazione_regione'] == 'Lombardia')]
data_region_Marche = data_region[(data_region['denominazione_regione'] == 'Marche')]
data_region_Molise = data_region[(data_region['denominazione_regione'] == 'Molise')]
data_region_Piemonte = data_region[(data_region['denominazione_regione'] == 'Piemonte')]
data_region_Puglia = data_region[(data_region['denominazione_regione'] == 'Puglia')]
data_region_Sardegna = data_region[(data_region['denominazione_regione'] == 'Sardegna')]
data_region_Sicilia = data_region[(data_region['denominazione_regione'] == 'Sicilia')]
data_region_Toscana = data_region[(data_region['denominazione_regione'] == 'Toscana')]
data_region_Trento = data_region[(data_region['denominazione_regione'] == 'P.A. Trento')]
data_region_Umbria = data_region[(data_region['denominazione_regione'] == 'Umbria')]
data_region_VAosta = data_region[(data_region['denominazione_regione'] == "Valle d'Aosta")]
data_region_Veneto = data_region[(data_region['denominazione_regione'] == 'Veneto')]

def region_apply(region):
    for x in region:
        x['new_cases'] =  x['totale_casi'].diff()
        x['new_deaths'] = x['deceduti'].diff()
        x['new_recovered'] = x['dimessi_guariti'].diff()
        x['new_swabs'] = x['tamponi'].diff()
        #add a day/day-1 percentage change for new_cases
        x['daily_cases_perc_change'] = round((x['new_cases'].pct_change(1))*100,2)
        x['daily_swab_perc_change'] = round((x['new_swabs'].pct_change(1))*100,2)
        #detect ratio
        x['detect_ratio'] = round((x['new_cases'] / x['new_swabs'])*100,2)
        return; 

region_apply([data_region_Abruzzo])  
region_apply([data_region_Basilicata]) 
region_apply([data_region_Bolzano])
region_apply([data_region_Calabria])
region_apply([data_region_Campania])
region_apply([data_region_EmiliaR])
region_apply([data_region_Friuli])
region_apply([data_region_Lazio])
region_apply([data_region_Liguria])
region_apply([data_region_Lombardia])
region_apply([data_region_Marche])
region_apply([data_region_Molise])
region_apply([data_region_Piemonte])
region_apply([data_region_Puglia])
region_apply([data_region_Sardegna])
region_apply([data_region_Sicilia])
region_apply([data_region_Toscana])
region_apply([data_region_Trento])
region_apply([data_region_VAosta])
region_apply([data_region_Veneto])
In [7]:
data_region_Nordovest = data_region[(data_region.denominazione_regione.isin(['Piemonte', 'Lombardia', 'Liguria',"Valle d'Aosta"]))]
data_region_Nordest = data_region[(data_region.denominazione_regione.isin(['Emilia-Romagna', 'P.A. Bolzano', 'P.A. Trento', 'Veneto', 'Friuli Venezia Giulia']))]
data_region_Centro = data_region[(data_region.denominazione_regione.isin(['Toscana', 'Umbria', 'Marche', 'Lazio']))]
data_region_Sudisole = data_region[(data_region.denominazione_regione.isin(['Abruzzo', 'Molise', 'Campania', 'Puglia', 'Basilicata', 'Calabria', 'Sicilia', 'Sardegna']))]

cases_Nordovest = data_region_Nordovest.groupby('data').sum()
region_apply([cases_Nordovest])  
cases_Nordovest['data'] = cases_Nordovest.index

cases_Nordest = data_region_Nordest.groupby('data').sum()
region_apply([cases_Nordest])  
cases_Nordest['data'] = cases_Nordest.index

cases_Centro = data_region_Centro.groupby('data').sum()
region_apply([cases_Centro])  
cases_Centro['data'] = cases_Centro.index

cases_Sudisole = data_region_Sudisole.groupby('data').sum()
region_apply([cases_Sudisole])  
cases_Sudisole['data'] = cases_Sudisole.index

cases_Nordovest.tail(5)
Out[7]:
codice_regione lat long ricoverati_con_sintomi terapia_intensiva totale_ospedalizzati isolamento_domiciliare totale_positivi variazione_totale_positivi nuovi_positivi ... tamponi casi_testati new_cases new_deaths new_recovered new_swabs daily_cases_perc_change daily_swab_perc_change detect_ratio data
data
2020-10-17T17:00:00 13 180.689065 33.123883 2025 187 2212 32309 34521 3712 4178 ... 3726942 2263052.0 4178.0 16.0 450.0 45713.0 8.46 0.58 9.14 2020-10-17T17:00:00
2020-10-18T17:00:00 13 180.689065 33.123883 2267 206 2473 34941 37414 2893 4541 ... 3771332 2291990.0 4541.0 26.0 1622.0 44390.0 8.69 -2.89 10.23 2020-10-18T17:00:00
2020-10-19T17:00:00 13 180.689065 33.123883 2481 212 2693 37117 39810 2396 3078 ... 3797797 2309178.0 3078.0 16.0 666.0 26465.0 -32.22 -40.38 11.63 2020-10-19T17:00:00
2020-10-20T17:00:00 13 180.689065 33.123883 2846 222 3068 40327 43395 3585 4401 ... 3839186 2334090.0 4401.0 31.0 785.0 41389.0 42.98 56.39 10.63 2020-10-20T17:00:00
2020-10-21T17:00:00 13 180.689065 33.123883 3221 244 3465 45312 48777 5382 6581 ... 3895718 2369221.0 6581.0 36.0 1163.0 56532.0 49.53 36.59 11.64 2020-10-21T17:00:00

5 rows × 25 columns

Andamento Nazionale

In [8]:
fig2 = px.bar(data_national, x='data', y='totale_casi',
             hover_data=['totale_casi'], color='totale_casi',
             height=600, color_continuous_scale='Sunsetdark')

fig2.update_layout(title_text='Total COVID19 Cases - Italy',
                  xaxis_rangeslider_visible=True)
fig2.update_yaxes(tick0=0, dtick=25000,  gridcolor='White')
fig2.show()
In [9]:
fig22 = px.bar(data_national, x='data', y='totale_positivi',
             hover_data=['totale_positivi'], color='totale_positivi',
             height=600, color_continuous_scale='Sunsetdark')

fig22.update_layout(title_text='Active COVID19 Cases - Italy',
                  xaxis_rangeslider_visible=True)
fig22.update_yaxes(tick0=0, dtick=10000,  gridcolor='White')
fig22.show()

Andamento per zone d'Italia

In [10]:
fig = go.Figure()

fig.add_trace(go.Scatter(mode = "lines+markers", x=cases_Nordovest['data'], y=cases_Nordovest['new_cases'], name="North-West",
                         line_color='red'))
fig.add_trace(go.Scatter(mode = "lines+markers", x=cases_Nordest['data'], y=cases_Nordest['new_cases'], name="North-East",
                         line_color='green'))
fig.add_trace(go.Scatter(mode = "lines+markers", x=cases_Centro['data'], y=cases_Centro['new_cases'], name="Center",
                         line_color='darkviolet'))
fig.add_trace(go.Scatter(mode = "lines+markers", x=cases_Sudisole['data'], y=cases_Sudisole['new_cases'], name="South and Islands",
                         line_color='darkblue'))
fig.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['new_cases'], name="All Italy",
                         line_color='deepskyblue'))

fig.update_layout(title_text='Daily Coronavirus new cases - All Italy and Regions',
                  xaxis_rangeslider_visible=True)


fig.show()
In [11]:
fig = go.Figure()

fig.add_trace(go.Scatter(mode = "lines+markers", x=cases_Nordovest['data'], y=cases_Nordovest['new_swabs'], name="North-West",
                         line_color='red'))
fig.add_trace(go.Scatter(mode = "lines+markers", x=cases_Nordest['data'], y=cases_Nordest['new_swabs'], name="North-East",
                         line_color='green'))
fig.add_trace(go.Scatter(mode = "lines+markers", x=cases_Centro['data'], y=cases_Centro['new_swabs'], name="Center",
                         line_color='darkviolet'))
fig.add_trace(go.Scatter(mode = "lines+markers", x=cases_Sudisole['data'], y=cases_Sudisole['new_swabs'], name="South and Islands",
                         line_color='darkblue'))
fig.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['new_swabs'], name="All Italy",
                         line_color='deepskyblue'))

fig.update_layout(title_text='Daily swabs - All Italy and Regions',
                  xaxis_rangeslider_visible=True)


fig.show()
In [12]:
fig = go.Figure()


fig.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['new_deaths'], name="Daily Deaths",
                         line_color='red'))
fig.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['new_recovered'], name="Daily Recovered",
                         line_color='green'))



fig.update_layout(title_text='Daily Coronavirus Deaths and Recoveries - Italy',
                  xaxis_rangeslider_visible=True)

fig.update_yaxes(tick0=0, dtick=500)

fig.show()
In [13]:
fig.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['new_cases'], name="Daily Cases",
                         line_color='deepskyblue'))
fig.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['new_swabs'], name="Daily swabs",
                         line_color='purple'))
fig.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['new_unique_tested'], name="Daily unique tested",
                         line_color='red'))
fig.update_layout(title_text='Daily Coronavirus new cases and swabs - Italy',
                  xaxis_rangeslider_visible=True)

fig.update_yaxes(tick0=0, dtick=10000)

fig.show()
In [14]:
fig3 = go.Figure()

fig3.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['detect_ratio_swabs'], name="Daily detect ratio - Italy",
                         line_color='purple'))
fig3.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['detect_ratio_cases'], name="Daily unique detect ratio - Italy",
                         line_color='red'))


fig3.update_layout(title_text="Daily Swabs detect ratio - Italy",
                  xaxis_rangeslider_visible=True)
fig3.update_yaxes(dtick=5)
In [15]:
fig4 = go.Figure()

#fig4.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['terapia_intensiva'], name="Daily total UTI - Italy",
#                         line_color='blue'))
fig4.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['totale_ospedalizzati'], name="Daily total Hospital - Italy",
                         line_color='green'))

fig4.update_layout(title_text="Daily Total Hospital - Italy",
                  xaxis_rangeslider_visible=True)
fig4.update_yaxes(dtick=2000)
In [16]:
fig5 = go.Figure()

fig5.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['terapia_intensiva'], name="Daily total UTI - Italy",
                         line_color='blue'))

fig5.update_layout(title_text="Daily Total UTI - Italy",
                  xaxis_rangeslider_visible=True)
fig5.update_yaxes(dtick=200)
In [17]:
fig6 = go.Figure()

fig6.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['daily_cases_perc_change'], name="Daily cases percentual change - Italy",
                         line_color='purple'))
fig6.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['daily_swab_perc_change'], name="Daily swab percentual change - Italy",
                         line_color='red'))


fig6.update_layout(title_text="Daily v- Italy",
                  xaxis_rangeslider_visible=True)
fig6.update_yaxes(dtick=40)
In [18]:
fig7 = go.Figure()

fig7.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['new_recovered'], name="Daily new recovered - Italy",
                         line_color='purple'))
fig7.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['new_deaths'], name="Daily new deaths - Italy",
                         line_color='red'))
fig7.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['new_cases'], name="Daily new cases - Italy",
                         line_color='green'))

fig7.update_layout(title_text="Daily change - Italy",
                  xaxis_rangeslider_visible=True)
fig7.update_yaxes(dtick=500)
In [19]:
fig8 = go.Figure()

fig8.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['terapia_intensiva'], name="Daily total UTI - Italy",
                         line_color='purple'))
fig8.add_trace(go.Scatter(mode = "lines+markers", x=data_national['data'], y=data_national['new_deaths'], name="Daily new deaths - Italy",
                         line_color='red'))


fig8.update_layout(title_text="Daily UTI vs  Death - Italy",
                  xaxis_rangeslider_visible=True)
fig8.update_yaxes(dtick=200)

Andamento Provincia di Genova

In [20]:
data_ge=data_province[data_province['sigla_provincia']=='GE']
#print(data_ge)
fig9 = go.Figure()

fig9.add_trace(go.Scatter(mode = "lines+markers", x=data_ge['data'], y=data_ge['totale_casi'], name="Daily cases GE - Italy",
                         line_color='red'))



fig9.update_layout(title_text="Daily cases GE - Italy",
                  xaxis_rangeslider_visible=True)
fig9.update_yaxes(dtick=1000)

Andamento Regionale

In [21]:
fig10 = go.Figure()

fig10.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['totale_casi'], name="Daily cases Liguria - Italy",
                         line_color='red'))



fig10.update_layout(title_text="Daily cases Liguria - Italy",
                  xaxis_rangeslider_visible=True)
fig10.update_yaxes(dtick=1000)
In [22]:
fig11 = go.Figure()

fig11.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['terapia_intensiva'], name="Daily UTI Liguria - Italy",
                         line_color='red'))
fig11.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['ricoverati_con_sintomi'], name="Daily hospital Liguria - Italy",
                         line_color='purple'))
fig11.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['new_deaths'], name="Daily new deaths Liguria - Italy",
                         line_color='green'))
fig11.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['nuovi_positivi'], name="Daily new cases Liguria - Italy",
                         line_color='blue'))
#fig11.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['new_swabs'], name="Daily new swabs Liguria - Italy",
#line_color='black'))
fig11.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['new_recovered'], name="Daily new recovered Liguria - Italy",
                         line_color='yellow'))

fig11.update_layout(title_text="Daily change Liguria - Italy",
                  xaxis_rangeslider_visible=True)
fig11.update_yaxes(dtick=100)
In [23]:
fig12 = go.Figure()

#fig11.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['daily_cases_perc_change'], name="Daily UTI Liguria - Italy",
#                         line_color='red'))
#fig11.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['daily_swab_perc_change'], name="Daily hospital Liguria - Italy",
#                         line_color='purple'))
fig12.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['detect_ratio'], name="Daily detect  ratio Liguria - Italy",
                         line_color='green'))
#fig11.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['nuovi_positivi'], name="Daily new cases Liguria - Italy",
#                         line_color='blue'))
#fig11.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['new_swabs'], name="Daily new swabs Liguria - Italy",
#line_color='black'))
#fig11.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['new_recovered'], name="Daily new recovered Liguria - Italy",
#                         line_color='yellow'))

fig12.update_layout(title_text="Daily detect ratio Liguria - Italy",
                  xaxis_rangeslider_visible=True)
fig12.update_yaxes(dtick=20)
In [24]:
fig13 = go.Figure()

fig13.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['daily_cases_perc_change'], name="Daily cases perc change Liguria - Italy",
                         line_color='red'))
fig13.add_trace(go.Scatter(mode = "lines+markers", x=data_region_Liguria['data'], y=data_region_Liguria['daily_swab_perc_change'], name="Daily swab perc change Liguria - Italy",
                         line_color='purple'))


fig13.update_layout(title_text="Daily percentual change Liguria - Italy",
                  xaxis_rangeslider_visible=True)
fig13.update_yaxes(dtick=100)
In [25]:
#print(data_national.dtypes)
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